G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS

G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects

G06K9/00785—Recognising traffic patterns acquired by static cameras

G—PHYSICS

G06—COMPUTING; CALCULATING; COUNTING

G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS

G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects

G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes

G06K9/00798—Recognition of lanes or road borders, e.g. of lane markings, or recognition of driver's driving pattern in relation to lanes perceived from the vehicle; Analysis of car trajectory relative to detected road

G—PHYSICS

G06—COMPUTING; CALCULATING; COUNTING

G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS

G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects

G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes

G06K9/00805—Detecting potential obstacles

G—PHYSICS

G06—COMPUTING; CALCULATING; COUNTING

G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS

G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects

G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes

G06K9/00818—Recognising traffic signs

G—PHYSICS

G06—COMPUTING; CALCULATING; COUNTING

G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS

G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects

G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes

G06K9/00825—Recognition of vehicle or traffic lights

Abstract

Translated from Chinese

本申请公开了应用于无人驾驶汽车的测试场景构建方法和装置。 The present application discloses an unmanned vehicle test scenarios applied to construction methods and apparatus.该方法的一具体实施方式包括：获取包含场景对象的路况图像，场景对象包括：道路对象、交通标识对象、车辆对象、行人对象；基于路况图像，获取场景对象的属性信息；基于场景对象和属性信息，构建无人驾驶汽车的测试场景。 A specific embodiment of the method comprising: obtaining traffic images comprising objects in the scene, the scene object comprises: a road objects, traffic identifies the object, the vehicle object pedestrians objects; based on the scene objects and attributes; based on the road image, acquiring the attribute information of objects in the scene information, build driverless cars test scenarios.实现了利用真实的道路对象、交通标识对象、车辆对象、行人对象的属性构建无人驾驶汽车的测试场景，从而还原出真实的路况作为无人驾驶汽车的测试场景，进而提升对无人驾驶汽车的测试的准确性。 We can use the real objects of the road, traffic signs objects, vehicles objects, properties, objects to build a pedestrian driverless car test scenarios, thus reducing the real road conditions as a driverless car test scenarios, and thus enhance the unmanned car the accuracy of the test.

Description

[0001]本申请涉及人工智能领域，具体涉及无人驾驶汽车领域，尤其涉及应用于无人驾驶汽车的测试场景构建方法和装置。 [0001] The present application relates to the field of artificial intelligence, particularly relates to unmanned vehicles, and more particularly relates to unmanned vehicle test scenarios applied to construction methods and apparatus.

背景技术 Background technique

[0002]车辆测试是提升车辆安全性的重要手段。 [0002] vehicle testing is an important means to enhance vehicle safety.在对车辆进行测试时，需要设置包含道路、车辆、行人等元素的测试场景，然后，对测试场景进行仿真，完成对车辆的测试。 When the vehicle testing, need to set up test scenarios include roads, vehicles, pedestrians and other elements, then, to test scenarios for simulation, complete testing of the vehicle.目前，在设置测试场景时，通常米用的方式为：以人工方式设置场景中的各个元素的位置、速度等属性。 At present, when setting up the test scenario, commonly used in rice way: to manually set the position of each element in the scene, the speed and other attributes.

[0003]然而，当采用上述方式设置测试场景时，一方面，需要针对每一个元素的属性，设置元素所有可能出现的数值，导致开销巨大。 [0003] However, when the above test scenario provided, on the one hand, the properties required for each element, the element is provided for all possible values, resulting in large overhead.另一方面，任意元素的属性因人工设置而引起的与实际情况的误差均会进一步增加整个测试场景的误差，导致测试场景失真，进而降低车辆测试的准确性。 On the other hand, due to the properties of any element caused by the manual setting of the error situation will further increase the variation in the entire test scenario, the test scenario leads to distortion, thereby reducing the accuracy of the test vehicle.

发明内容 SUMMARY

[0004]本申请提供了应用于无人驾驶汽车的测试场景构建方法和装置，用于解决上述背景技术部分存在的技术问题。 [0004] The present application provides an unmanned vehicle test scenarios applied to construct a method and apparatus for solving the above technical problem exists in the Background section.

[0005]第一方面，本申请提供了应用于无人驾驶汽车的测试场景构建方法，该方法包括： 获取包含场景对象的路况图像，场景对象包括:道路对象、交通标识对象、车辆对象、行人对象;基于路况图像，获取场景对象的属性信息;基于场景对象和属性信息，构建无人驾驶汽车的测试场景。 [0005] In a first aspect, the present application provides applied constructed unmanned vehicle test scenarios, the method comprising: obtaining an image comprising a traffic scene objects, the scene object comprises: a road objects, the object traffic signs, vehicle objects, pedestrians the object; an image based on road conditions, access to property information of the object scene; a scene based on the object and attribute information to build an unmanned vehicle test scenarios.

[0007]本申请提供的应用于无人驾驶汽车的测试场景构建方法和装置，通过获取包含场景对象的路况图像，场景对象包括:道路对象、交通标识对象、车辆对象、行人对象;基于路况图像，获取场景对象的属性信息;基于场景对象和属性信息，构建无人驾驶汽车的测试场景。 [0007] The present application is applied to provide unmanned vehicle test scenarios construction method and apparatus, comprising an image by acquiring traffic scene objects, the scene object comprises: a road objects, the object traffic signs, vehicle objects, the object pedestrians; traffic based on the image to obtain the object scene attribute information; scene objects and attribute information to build an unmanned vehicle test scenarios based.实现了利用真实的道路对象、交通标识对象、车辆对象、行人对象的属性构建无人驾驶汽车的测试场景，从而还原出真实的路况作为无人驾驶汽车的测试场景，进而提升对无人驾驶汽车的测试的准确性。 We can use the real objects of the road, traffic signs objects, vehicles objects, properties, objects to build a pedestrian driverless car test scenarios, thus reducing the real road conditions as a driverless car test scenarios, and thus enhance the unmanned car the accuracy of the test.

附图说明 BRIEF DESCRIPTION

[0008]通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本申请的其它特征、目的和优点将会变得更明显： [0008] The accompanying drawings by reading the following detailed description of non-limiting embodiments, and other features, objects and advantages of the present disclosure will become more apparent:

[0009] 图1示出了根据本申请的应用于无人驾驶汽车的测试场景构建方法的一个实施例的流程图； [0009] FIG. 1 shows a flow diagram of one embodiment of a method constructed in accordance with the present application is applied to driverless vehicle test scenarios;

[0010] 图2示出了本申请中的对无人驾驶汽车的测试场景进行仿真的一个示例性原理图； [0010] FIG 2 illustrates a test scenario for the unmanned vehicle according to the present application is an exemplary schematic diagram of the simulation;

[0011] 图3示出了根据本申请的应用于无人驾驶汽车的测试场景构建装置的一个实施例的结构示意图； [0011] FIG. 3 shows a structure diagram of one embodiment of apparatus constructed in accordance with the present application is applied to the unmanned vehicle test scenarios;

[0012] 图4是适于用来实现本申请实施例的终端设备或服务器的计算机系统的结构示意图。 [0012] FIG. 4 is a schematic structural diagram of a computer system suitable for use in an embodiment of the present application achieved a terminal device or a server.

具体实施方式 Detailed ways

[0013] 下面结合附图和实施例对本申请作进一步的详细说明。 Drawings and embodiments of the present application will be further described in detail [0013] below in conjunction.可以理解的是，此处所描述的具体实施例仅仅用于解释相关发明，而非对该发明的限定。 It will be appreciated that the specific embodiments described herein are only relevant for explaining the invention, not limitation of the invention.另外还需要说明的是，为了便于描述，附图中仅示出了与有关发明相关的部分。 Also to be noted also that, for convenience of description, the accompanying drawings show only parts related to the related invention.

[0014] 需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。 [0014] Incidentally, in the case of no conflict, embodiments and features of the embodiments of the present application can be combined with each other.下面将参考附图并结合实施例来详细说明本申请。 Below with reference to the accompanying drawings and described in detail in conjunction with embodiments of the present application.

[0015] 请参考图1，其示出了根据本申请的应用于无人驾驶汽车的测试场景构建方法的一个实施例的流程100。 [0015] Please refer to FIG. 1, which shows a flow of one embodiment of a method constructed in accordance with the present application is applied to driverless vehicle test scenarios 100.该方法包括以下步骤： The method comprises the steps of:

[0017] 在本实施例中，可以预先选取出一些用于构建无人驾驶汽车的测试场景的场景对象，用于构建无人驾驶汽车的测试场景的场景对象可以包括但不限于:道路对象、交通标识对象、车辆对象、行人对象。 [0017] In the present embodiment, may be pre-selected scene object used to construct some of the unmanned vehicle test scenarios for building unmanned vehicle test scenarios scenario objects may include but are not limited to: the corridor object, traffic identify the object, the object vehicles, pedestrians object.

[0018] 在本实施例的一些可选的实现方式中，获取包含场景对象的路况图像包括:从第三方交通监控平台获取通过设置于城市道路的路口的摄像头采集到的路况图像。 [0018] some alternative implementations of the embodiments in the present embodiment, the acquired image comprising a traffic scene object comprises: acquiring captured by a camera provided on a city road intersection road traffic monitoring image from a third party internet.

[0019] 在本实施例中，路况图像可以为监控城市交通状况的第三方交通监控平台，例如交通管理局的交通监控平台通过设置于城市道路的各个路口的摄像头采集到的路况图像。 [0019] embodiment, the image may be a road traffic monitoring internet third party monitoring urban traffic conditions such as traffic monitoring platform Traffic Authority provided in the camera by each of the urban road intersection road image acquired in the present embodiment.设置于城市道路的各个路口的摄像头采集到的路况图像可以包含道路对象、道路上的交通标识对象、道路上的车辆对象、行人对象。 Set the camera on urban roads all the roads of the collected road image objects can contain roads, traffic signs objects on the road, vehicles object on the road, pedestrians object.交通标识对象可以包括但不限于:车道线、交通标志牌、指示标线、红绿灯。 Transportation to identify the object may include, but are not limited to: lane lines, traffic signs, indicative marking, traffic lights.

[0020] 步骤102，基于路况图像，获取场景对象的属性信息。 [0020] Step 102, based on the road image, acquiring the attribute information of the object scene.

[0022] 在本实施例中，在通过步骤101获取到包含道路对象、道路对象上的车辆对象、行人对象等场景对象的路况图像之后，可以基于路况图像，获取场景对象的属性信息。 [0022] In the present embodiment, at step 101 acquired by the object comprises a road, the road image of the scene after the vehicle target object, an object like a pedestrian on the road the object, based on the road image, acquiring the attribute information of the object scene.

[0023]在本实施例的一些可选的实现方式中，基于路况图像，获取场景对象的属性信息包括:从电子地图中获取与路况图像的拍摄位置对应的路段中的道路的拓扑结构、交通标识的位置;将拓扑结构、位置作为道路对象、交通标识对象的属性信息。 [0023] In some alternative implementations of the present embodiment, based on the road image, acquiring the attribute information of the object scene comprising: a topology of a road link corresponding to the imaging position acquired from the electronic map with road images of traffic location identification; the topology position as road objects, properties, traffic information identifying the object.

[0024]在本实施例中，可以根据路况图像的拍摄位置，确定电子地图中拍摄位置对应的路段。 [0024] In the present embodiment, according to the position of the road image capturing, determining a position corresponding to the photographing electronic map link.然后，可以在电子地图中获取拍摄位置对应的路段的道路的拓扑结构、道路上的交通标识以及交通标识在道路上的位置。 Then, you can obtain the topology of the road sections corresponding shooting position in the electronic map, traffic signs and traffic signs on the road position on the road.将道路的拓扑结构以及交通标识在道路上的位置作为道路对象、交通标识对象的属性信息。 The topology and traffic signs road position on the road as the road objects, properties, traffic information identifying the object.从而获取到道路对象、交通标识对象的属性信息。 In order to get to the road objects, properties, traffic information identifying the object.[0025]在本实施例的一些可选的实现方式中，基于路况图像，获取场景对象的属性信息包括:分别确定路况图像中每一帧路况图像中的车辆对象、行人对象的位置;基于每一帧路况图像中的车辆对象和行人对象的位置，分别计算车辆对象和行人对象的行进速度、行进方向、行进状态;将车辆对象和行人对象的行进速度、行进方向、行进状态作为车辆对象和行人对象的属性信息。 [0025] In some alternative implementations of the present embodiment, based on the road image, acquiring the attribute information of the object scene comprising: determining a position of the vehicle, respectively, each frame of image objects road traffic images, the object of the pedestrian; per a road position in the image of the vehicle object and the pedestrian object, calculates the traveling speed of the vehicle objects and pedestrians objects, traveling direction, the traveling state; and the traveling speed of the vehicle objects and pedestrians objects, traveling direction, the traveling state of the vehicle as the object and attribute information of the pedestrian object.

[0026] 在本实施例中，可以首先对路况图像中的车辆对象和行人对象进行识别。 [0026] In the present embodiment, the image may first road vehicles and pedestrians object recognition objects.例如，可以通过深度学习模型对路况图像中的车辆对象和行人对象进行识别。 For example, the image may be identified on the road a pedestrian and the vehicle target object through the depth of the learning model.在对路况图像中的车辆对象和行人对象进行识别之后，可以确定车辆对象和行人对象在图像中的位置。 After the image on the road a pedestrian and the vehicle target recognition object, the object can determine the location of the vehicle and the object in the image of a pedestrian.然后，可以根据车辆对象和行人对象在图像中的位置以及采集图像的摄像头对应的坐标系与车辆对象和行人对象的位置对应的坐标系之间的对应关系，计算出车辆对象和行人对象的位置。 Then, correspondence between may correspond to a vehicle according to the object and pedestrians target position in the image and the position captured by the camera image corresponding to the coordinate system of the vehicle objects and pedestrians object coordinate system, calculates the position of the vehicle objects and pedestrians object .

[0027] 在本实施例中，可以根据多个采集时间连续的路况图像中车辆对象和行人对象的位置，计算车辆对象和行人对象的行进速度、行进方向、行进状态。 [0027] In the present embodiment, the position of the temporally consecutive images of road vehicles and pedestrians objects may be acquired in accordance with a plurality of objects, calculates the traveling speed of the vehicle and the target object is a pedestrian, the traveling direction, the traveling state.然后，将计算出的车辆对象和行人对象的行进速度、行进方向、行进状态作为车辆对象和行人对象的属性信息。 Then, the traveling speed of the vehicle calculated target object and a pedestrian, the traveling direction, the traveling state of the vehicle as the attribute information of the object, and a pedestrian objects.从而获取到车辆对象和行人对象的行进速度、行进方向、行进状态等属性信息。 So as to acquire the traveling speed of the vehicle and the target object is a pedestrian, the traveling direction, the traveling status attribute information.

[0028]在本实施例中，可以采用以下方式计算行进速度、行进方向：以计算车辆对象的行进速度、行进方向为例，对于车辆对象的行进速度，可以获取分别获取多个采集时间连续的多帧路况图像中的第一帧路况图像中车辆的轮廓的中心点的坐标和最后一帧路况图像中车辆的轮廓的中心点的坐标。 [0028] In the present embodiment, the traveling speed may be calculated in the following manner, the traveling direction: the traveling speed of the vehicle is calculated at the object, the direction of travel, for example, the traveling speed of the vehicle to the object, may be acquired acquiring a plurality of successive acquisition times were the center point coordinates of the outline of the vehicle and the last image in a traffic center point of the contour of the vehicle frame of the first road traffic images of multiple frames of images.然后，可以计算上述最后一个路况图像中车辆的轮廓的中心点的坐标与第一个路况图像中车辆的轮廓的中心点的坐标的差值。 Then, the coordinates of the center point can calculate the difference of the coordinates of the outline of a road center of the image contour of the road image, the last vehicle in the vehicle.可以将该差值除多个采集时间连续的多帧路况图像对应的采集时间，即可得到该时间段内的车辆的平均速度。 The difference may be in addition to a plurality of successive acquisition times corresponding to a plurality of frames of traffic image acquisition time, the average speed of the vehicle can be obtained over the time period.对于车辆对象的行进方向，可以根据车道线位置与车辆的位置，确定车辆的位置与车道线的偏移量，从而根据该偏移量，确定车辆的行进方向。 For the traveling direction of the subject vehicle, the position of the vehicle may determine the lane line position and the shift amount of the vehicle according to the lane line position, so that based on the offset, to determine the traveling direction of the vehicle.可以基于上述确定车辆对象的行进速度、行进方向的过程，确定行人对象的行进速度、行进方向。 Can be determined based on the traveling speed of the target vehicle, process the traveling direction, the traveling speed of the pedestrian is determined in the subject, the direction of travel.

[0029]在本实施例中，可以采用以下方式计算车辆对象和行人对象的行进状态：以计算车辆对象的行进状态为例，可以根据采集时间相邻的路况图像中车辆的轮廓的中心点的坐标的变化，判断车辆的状态。 [0029] In the present embodiment, the traveling state of the vehicle may be calculated target object and pedestrians in the following manner: an object in a traveling state of the vehicle is calculated as an example, the profile may be adjacent to the central point of the image according to the collected time road vehicle coordinates change, determines the state of the vehicle.例如，当两个采集时间相邻的路况图像中车辆的轮廓的中心点的坐标的变化小于阈值时，可以判断车辆对象进行了刹车，则车辆对象的行进状态可以为刹车状态。 For example, when the change of the coordinates of the center point of the contour of the road two adjacent image acquisition time the vehicle is less than a threshold, the object can be determined that the vehicle brakes, the traveling state of the vehicle may brake state object.可以基于上述确定车辆对象的行进状态的过程，确定行人对象的行进状态。 The process may be based on the traveling state of the vehicle to determine an object, the object to determine the traveling state of the pedestrian.

[0031] 在本实施例中，可以在通过步骤102获取场景对象的属性信息，例如，道路对象的拓扑结构、交通标识对象的位置、车辆对象和行人对象的行进速度、行进方向、行进状态之后，可以利用道路对象、交通标识对象、车辆对象、行人对象等场景对象以及道路对象、交通标识对象、车辆对象、行人对象的属性信息，构建无人驾驶汽车的测试场景。 After [0031] In the present embodiment, may be 102 acquires attribute information of the objects in the scene by step, for example, the topology of the road the object, position of the vehicle identifies the object, the traveling speed of the vehicle objects and pedestrians objects, traveling direction, the traveling state , you can use the object road, traffic identifies the object, the object vehicles, pedestrians, objects and other scene objects and objects of road, traffic identifies the object, the object vehicles, pedestrians object attribute information to build driverless cars test scenarios.从而，在构建出的测试场景中，道路对象的拓扑结构为真实道路的拓扑结构，交通标识对象的位置为交通标识对象在道路中的真实位置，车辆和行人的行进速度、行进方向、行进状态则为真实的车辆和行人的行进速度、行进方向、行进状态。 Thus, in the construction of a test scenario, topology road object to the topology of real roads, location of traffic identifies the object as a true position of the vehicle to identify the object in the road, the traveling speed of the vehicle and the pedestrian, the direction of travel, the traveling state It was true of the travel speed of vehicles and pedestrians, direction of travel, the traveling state.从而还原出真实的路况，将真实的路况作为无人驾驶汽车的测试环境。 Thereby reducing the real road conditions, road conditions will be a real test environment as a driverless car.

[0032] 在本实施例的一些可选的实现方式中，在基于场景对象和属性信息，构建无人驾驶汽车的测试场景之后，还包括:基于属性信息，配置仿真器中与场景对象对应的仿真对象的属性;利用仿真器基于仿真对象对无人驾驶汽车的测试场景进行仿真。 [0032] some alternative implementations of the embodiments in the present embodiment, after the object based on the scene and the attribute information, test scenario constructed unmanned vehicle, further comprising: based on the attribute information, configure the emulator corresponding to the object in the scene property simulation object; use the simulator to test driverless car simulation scenarios based on simulation object.

[0034] 在本实施例中，在构建出测试场景之后，可以通过仿真器对构建出的无人驾驶汽车的测试场景进行仿真，从而在真实的路况中对无人驾驶汽车进行测试。 [0034] In the present embodiment, constructed after the test scenario may be constructed to simulate the unmanned vehicle through the simulator test scenario to be tested in a real unmanned vehicles in the road.

[0035] 在本实施例中，仿真器可以为开源车辆测试环境仿真框架OpenDrive框架。 [0035] In the present embodiment, the emulator may be an open source environment simulation test vehicle frame OpenDrive frame.在OpenDrive框架中，包含道路对象对应的仿真对象、交通标识对象对应的仿真对象、车辆对象对应的仿真对象、自定义的类型的仿真对象，例如行人对象对应的仿真对象。 In OpenDrive frame, comprising a road simulation object corresponding to the object, identifies the object corresponding to the traffic simulation object, the vehicle simulation object corresponding to the object, since the simulation object type definitions, for example, a pedestrian simulation object corresponding to the object.

[0036] 在对无人驾驶汽车的测试环境进行仿真时，可以首先在OpenDrive框架中创建道路对象、交通标识对象、车辆对象、行人对象对应的仿真对象。 [0036], you can first create an object in the road OpenDrive frame at the time of the unmanned vehicle simulation testing environment, transportation identify the object, the object vehicles, pedestrians objects corresponding simulation object.然后，可以利用获取到道路对象、交通标识对象、车辆对象、行人对象配置仿真对象的属性。 Then, you can use the road to get the object, traffic sign an object, the object vehicle, pedestrian simulation object configuration attributes of the object.例如，可以将获取到道路对象、交通标识对象、车辆对象、行人对象的属性信息赋值给对应的仿真对象的相应的属性。 For example, you can get to the object road, traffic identifies the object, the object vehicle, pedestrian object attribute information assigned to the corresponding property of corresponding simulation object.从而，在利用OpenDrive框架对构建出的无人驾驶汽车的测试场景进行仿真时，可以利用配置后的各个仿真对象还原出真实的道路对象的拓扑结构、交通标识对象在道路中的真实位置、真实的车辆和行人的行进速度、行进方向、行进状态。 Therefore, when constructing a driverless car test scenarios to simulate the use of OpenDrive framework that can be used after each simulation object configuration restore the true topology of the road objects, traffic signs object in the real position in the road, real the traveling speed of the vehicle and the pedestrian, traveling direction, traveling state.从而还原出真实的路况，将真实的路况作为无人驾驶汽车的测试环境，进而提升对无人驾驶汽车的测试的准确性。 Thereby reducing the real road conditions, road conditions as the real driverless car test environment, thereby enhancing the accuracy of the test driverless cars.

[0038] 在对无人驾驶汽车的测试场景进行仿真时，可以首先获取到设置在城市道路的路口上的摄像头采集到的路况图像。 [0038] at the time of the unmanned vehicle simulation test scenarios can be first to get the camera set up on a city road intersection of the collected road image.在获取到设置在城市道路的路口上的摄像头采集到的路况图像之后，可以获取真实道路、交通标识、车辆、行人对象的属性，即获取道路对象、交通标识对象、车辆对象、行人对象的属性信息。 After obtaining the camera settings on the intersection of urban roads of the collected road image, you can get real roads, traffic signs, vehicles, property pedestrian objects that get road objects, properties, traffic signs objects, vehicles objects, pedestrians object information.道路对象的属性信息包括道路对象的拓扑结构、交通标识对象的属性信息包括交通标识对象的位置。 Object property information includes topology road road object, object attribute information including the location of traffic signs traffic signs object.车辆对象和行人对象的属性信息包括车辆对象和行人对象的行进速度、行进方向、行进状态。 Attribute information of the object vehicle and pedestrian object comprises traveling speed of the vehicle and the target object is a pedestrian, the traveling direction, the traveling state.

[0039]可以根据道路对象、交通标识对象、车辆对象、行人对象等场景对象以及获取到的道路对象、交通标识对象、车辆对象、行人对象等场景对象的属性信息，构建无人驾驶汽车的测试场景，该测试场景也称之为仿真场景。 [0039] According to the attribute information of the scene may object objects road, traffic identifies the object, the object vehicles, pedestrians, objects and other scene objects and access road to the object, traffic sign an object, the object vehicles, pedestrians and other objects, build driverless car test scene, also known as the test scenario simulation scenarios.仿真场景中包含真实的道路的拓扑结构、交通标识在道路上所处的真实位置、道路上的车辆对象、行人对象真实的行进速度、行进方向、 行进状态。 Simulation scenarios include the real road topology, traffic signs on the road in which the real position of the object vehicle on the road, pedestrians real objects traveling speed, direction of travel, the traveling state.

[0040] 可以基于不同的路段中的道路对象、交通标识对象、车辆对象、行人对象的属性， 构建多个不同的仿真场景。 [0040] can be based on different sections of the object in the road, traffic identifies the object, vehicle objects, properties, pedestrian objects, building a number of different simulation scenarios.在构建多个不同的仿真场景之后，可以利用仿真器对不同的仿真场景进行仿真。 After building a plurality of different simulation scenarios, different simulation scenarios can be simulated using the simulator.从而还原出真实的路况，将真实的路况作为无人驾驶汽车的测试场景，完成对无人驾驶汽车的测试。 Thereby reducing the real road conditions, road conditions as the real test driverless car scene, complete testing of unmanned vehicles.

[0041] 请参考图3,作为对上述各图所示方法的实现，本申请提供了一种应用于无人驾驶汽车的测试场景构建装置的一个实施例，该装置实施例与图1所示的方法实施例相对应，该装置具体可以应用于各种电子设备中。 [0041] Please refer to FIG. 3, there is provided an unmanned vehicle test scenarios applied to construct an apparatus to realize the above-described embodiment examples shown in the figures the method of the present application, the apparatus of the embodiment 1 shown in FIG. the method of Example corresponds embodiment, the apparatus may be specifically applied to various electronic devices.

[0043] 在本实施例的一些可选的实现方式中，图像获取单元301包括:路况图像获取子单元，配置用于从第三方交通监控平台获取通过设置于城市道路的路口的摄像头采集到的路况图像。 [0043] some alternative implementations of the embodiments in the present embodiment, the image acquisition unit 301 comprises: an image acquisition sub-unit road, configured to obtain from a third party by the acquired internet traffic monitoring camera is provided on a city road intersection traffic image.

[0044] 在本实施例的一些可选的实现方式中，属性信息获取单元302包括:第一属性信息获取子单元(未示出），配置用于从电子地图中获取与路况图像的拍摄位置对应的路段中的道路的拓扑结构、交通标识的位置;第一属性信息配置子单元(未示出），配置用于将拓扑结构、位置作为道路对象、交通标识对象的属性信息。 [0044] In some alternative implementations of the present embodiment, the attribute information acquisition unit 302 includes: a first sub-attribute information acquiring unit (not shown) configured for obtaining imaging position from an electronic map with road images in a position corresponding to the road link topology, traffic sign; attribute information of a first sub-unit configuration (not shown), configured to topology, as the road position of the object, the object attribute information of a traffic sign.

[0045]在本实施例的一些可选的实现方式中，属性信息获取单元302包括:第二属性信息获取子单元(未示出），配置用于分别确定路况图像中每一帧路况图像中的车辆对象和行人对象的位置;计算子单元(未示出），配置用于基于每一帧路况图像中的车辆对象和行人对象的位置，分别计算车辆对象和行人对象的行进速度、行进方向、行进状态;第二属性信息配置子单元(未示出），配置用于将车辆对象和行人对象的行进速度、行进方向、行进状态作为车辆对象和行人对象的属性信息。 [0045] In some alternative implementations of the present embodiment, the attribute information acquisition unit 302 includes: a second attribute information obtaining sub-unit (not shown), configured for respectively determining road traffic images in each frame image target position of the vehicle and a pedestrian object; calculating sub-unit (not shown) configured to traveling speed of the vehicle based on the position of the target object and the pedestrian road image in each frame, and calculates the vehicle target object pedestrian, the traveling direction , the traveling state; a second sub-unit attribute information of the configuration (not shown), the traveling speed of the vehicle arranged for a pedestrian and the subject object, the traveling direction, the traveling state of the vehicle as the attribute information of the object, and a pedestrian objects.

[0048]图4示出了适于用来实现本申请实施例的终端设备或服务器的计算机系统的结构不意图。 [0048] FIG. 4 shows the structure of the present application is adapted to implement a terminal device or a server computer system according to the embodiment are not intended.

[0049]如图4所示，计算机系统400包括中央处理单元(CPU) 401，其可以根据存储在只读存储器(ROM) 402中的程序或者从存储部分408加载到随机访问存储器(RAM) 403中的程序而执行各种适当的动作和处理。 [0049] As shown, the computer system 400 includes a central processing unit (CPU) 401, which may or load 402 in accordance with a program stored in a read only memory (ROM) from the storage section 408 into a random access memory (RAM) 403 the program to perform various processing and appropriate action.在RAM403中，还存储有系统400操作所需的各种程序和数据。 In the RAM403, the desired 400 also stores various programs and operating system data.CPU401、R0M 402以及RAM 403通过总线404彼此相连。 CPU401, R0M 402 and RAM 403 are connected through a bus 404.输入/输出（I/O)接口405也连接至总线404。 Input / Output (I / O) interface 405 is also connected to the bus 404.

[0050]以下部件连接至I/O接口4〇5:包括键盘、鼠标等的输入部分406;包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分407;包括硬盘等的存储部分408; 以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分409。 [0050] The following components are connected to the I / O interface 4〇5: includes an input keyboard, a mouse portion 406; such as a cathode ray tube comprising (CRT), liquid crystal display (LCD) and the like, and a speaker section 407 outputting the like; includes a hard disk the storage section 408 and the like; and includes a communication such as a LAN card, a modem, a network interface card portion 409.通信部分709经由诸如因特网的网络执行通信处理。 The communication section 709 performs communication processing via a network such as the Internet.驱动器410也根据需要连接至I/O接口405。 Driver 410 is also connected to the I / O interface 405 as needed.可拆卸介质411，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器410上，以便于从其上读出的计算机程序根据需要被安装入存储部分408。 Removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., according to need is mounted on the drive 410, so that a computer program read out therefrom is installed into the storage section 408 as necessary.

[0051] 特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。 [0051] In particular, according to embodiments of the present disclosure, the process described above with reference to the flowchart may be implemented as computer software program.例如，本公开的实施例包括一种计算机程序产品，其包括有形地包含在机器可读介质上的计算机程序，所述计算机程序包含用于执行流程图所示的方法的程序代码。 For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly comprising readable medium on a machine, the computer program comprising program code for performing the method is shown in the flowchart.在这样的实施例中，该计算机程序可以通过通信部分409从网络上被下载和安装，和/或从可拆卸介质411被安装D In such an embodiment, the computer program may be downloaded via the communication section 409 from the network and installation, and / or from the removable medium 411 is mounted D

[0052]附图中的流程图和框图，图示了按照本申请各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。 [0052] The flowchart and block diagrams in the Figures illustrate a system according to an embodiment of the present application various, architecture methods and computer program products may implement the functions and operations.在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，所述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。 In this regard, the flowchart or block diagrams each block may represent a module, segment, or portion of code of a program, a module, segment, or which comprises one or a plurality of logic for implementing the specified executable instructions function.也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。 It should also be noted that, in some implementations Alternatively, the functions noted in the block may be different from the order noted in the figures occur.例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。 For example, two blocks shown in succession may in fact be executed substantially concurrently, they may sometimes be executed in the reverse order, depending upon the functionality involved may be.也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。 Also be noted that each block of the flowchart in block diagram, as well as combinations and / or block diagrams and / or flowchart block may perform a predetermined function or operation of dedicated hardware-based system to achieve , or may be special purpose hardware and computer instructions to implement.

[0053]作为另一方面，本申请还提供了一种非易失性计算机存储介质，该非易失性计算机存储介质可以是上述实施例中所述装置中所包含的非易失性计算机存储介质;也可以是单独存在，未装配入终端中的非易失性计算机存储介质。 [0053] As another aspect, the present application also provides a nonvolatile computer storage medium, the nonvolatile computer storage medium may be nonvolatile computer storage device of the above-described embodiments contained medium; may be present alone, it did not fit into nonvolatile computer storage media terminal.上述非易失性计算机存储介质存储有一个或者多个程序，当所述一个或者多个程序被一个设备执行时，使得所述设备:获取包含场景对象的路况图像，所述场景对象包括:道路对象、交通标识对象、车辆对象、行人对象;基于所述路况图像，获取所述场景对象的属性信息;基于所述场景对象和属性信息，构建无人驾驶汽车的测试场景。 The nonvolatile computer storage medium storing one or more programs, when the program is executed one or a plurality of apparatus, such that the apparatus: an image acquiring traffic scene comprising an object, the scene object comprises: a road object, traffic sign objects, objects vehicles, pedestrians objects; based on the road image, acquiring the attribute information of the object scene; and based on the attribute information of the object scene, constructing unmanned vehicle test scenarios.

[0054]以上描述仅为本申请的较佳实施例以及对所运用技术原理的说明。 Examples and description of the technical principles of the present disclosure use only the preferred embodiments [0054] described above.本领域技术人员应当理解，本申请中所涉及的发明范围，并不限于上述技术特征的特定组合而成的技术方案，同时也应涵盖在不脱离所述发明构思的情况下，由上述技术特征或其等同特征进行任意组合而形成的其它技术方案。 Those skilled in the art should understand that the scope of the present invention herein involved, is not limited to the particular combinations of the above aspect of the features formed, it should also be covered without departing from the spirit of the invention by the technical features or other technical equivalents solutions formed by any combination.例如上述特征与本申请中公开的(但不限于)具有类似功能的技术特征进行互相替换而形成的技术方案。 The above features and, for example, disclosed in the present application (without limitation) having technical features similar functionality to replace another aspect formed.

Claims (10)

Translated from Chinese

1. 一种应用于无人驾驶汽车的测试场景构建方法，其特征在于，所述方法包括： 获取包含场景对象的路况图像，所述场景对象包括:道路对象、交通标识对象、车辆对象、行人对象； 基于所述路况图像，获取所述场景对象的属性信息，基于所述路况图像，获取所述场景对象的属性信息包括:分别确定路况图像中每一帧路况图像中的车辆对象和行人对象的位置;基于每一帧路况图像中的车辆对象和行人对象的位置，分别计算车辆对象和行人对象的行进速度、行进方向、行进状态;将车辆对象和行人对象的行进速度、行进方向、行进状态作为车辆对象和行人对象的属性信息； 基于所述场景对象和属性信息，构建无人驾驶汽车的测试场景。 An unmanned vehicle test scenarios applied to construction method, characterized in that, said method comprising: obtaining an image comprising a traffic scene objects, the scene object comprises: a road objects, the object traffic signs, vehicle objects, pedestrians objects; based on the road image, acquiring the attribute information of the object scene based on the road image, acquiring the attribute information of the scene object comprises: determining respective target vehicle and pedestrian traffic the object image in each frame of traffic image position; the object based on the position of the vehicle and pedestrian traffic object image in each frame, calculate the traveling speed of the vehicle and the target object is a pedestrian, the traveling direction of the traveling condition; the traveling speed of the vehicle and the target object is a pedestrian, traveling direction, traveling Zhuangtai as attribute information of the object vehicle and pedestrian objects; and based on the attribute information of the object scene, constructing unmanned vehicle test scenarios.

2. 根据权利要求1所述的方法，其特征在于，所述获取包含场景对象的路况图像包括： 从第三方交通监控平台获取通过设置于城市道路的路口的摄像头采集到的路况图像。 2. The method according to claim 1, wherein said image comprises acquiring traffic scene object comprises: acquiring captured by a camera provided on a city road intersection road traffic monitoring image from a third party internet.

3. 根据权利要求1-2之一所述的方法，其特征在于，基于所述路况图像，获取所述场景对象的属性信息包括： 从电子地图中获取与所述路况图像的拍摄位置对应的路段中的道路的拓扑结构、交通标识的位置； 将所述拓扑结构、交通标识的位置作为所述道路对象、交通标识对象的属性信息。 3. The method according to one of claims 1-2, characterized in that, based on the road image, acquiring the attribute information of the scene object comprises: acquiring a position corresponding to the photographing of the image from the electronic road map the position of link topology, road traffic signs; the position of the topology of the road traffic sign as the object, the object attribute information of a traffic sign.

4. 根据权利要求1所述的方法，其特征在于，在基于所述场景对象和属性信息，构建无人驾驶汽车的测试场景之后，所述方法还包括： 基于所述属性信息，配置仿真器中与所述场景对象对应的仿真对象的属性； 利用所述仿真器基于所述仿真对象对无人驾驶汽车的测试场景进行仿真。 4. The method according to claim 1, wherein, after the scene based on the attribute information of the object and constructed unmanned vehicle test scenarios, the method further comprising: based on the attribute information, configure the emulator properties of the simulation object corresponding to the object scene; using said simulator based on the simulation object unmanned vehicle test scenarios simulated.

6. —种应用于无人驾驶汽车的测试场景构建装置，其特征在于，所述装置包括： 图像获取单元，配置用于获取包含场景对象的路况图像，所述场景对象包括：道路对象、交通标识对象、车辆对象、行人对象； 属性信息获取单元，配置用于基于所述路况图像，获取所述场景对象的属性信息，所述属性信息获取单元包括:第二属性信息获取子单元，配置用于分别确定路况图像中每一帧路况图像中的车辆对象和行人对象的位置;计算子单元，配置用于基于每一帧路况图像中的车辆对象和行人对象的位置，分别计算车辆对象和行人对象的行进速度、行进方向、行进状态;第二属性信息配置子单元，配置用于将车辆对象和行人对象的行进速度、行进方向、 行进状态作为车辆对象和行人对象的属性信息； 场景构建单元，配置用于基于所述场景对象和属性信息，构 6. - Species applied unmanned vehicle test scenarios construction apparatus, wherein, said apparatus comprising: an image acquisition unit configured to acquire traffic scene objects containing images, the scene object comprises: an object road, traffic identifying the object, the object vehicle, a pedestrian objects; attribute information obtaining unit configured to, based on the road image, acquiring the attribute information of the object scene, the attribute information obtaining unit comprises: a second attribute information obtaining sub-unit, configured with determining at each position of the object and the vehicle pedestrian traffic object image each frame of traffic image; calculating subunit, configured to objects based on the position of the vehicle and pedestrian traffic object in each frame image, and calculates target vehicle pedestrian the traveling speed of the object, the traveling direction of the traveling state; a second sub-unit attribute information of the configuration, the traveling speed of the vehicle arranged for a pedestrian and the subject object, the traveling direction, the traveling state of the vehicle as the attribute information of the object, and a pedestrian object; scene construction unit , based on the scene configuration information for the object and the properties, structure建无人驾驶汽车的测试场景。 Driverless cars built test scenarios.

7.根据权利要求6所述的装置，其特征在于，所述图像获取单元包括： 路况图像获取子单元，配置用于从第三方交通监控平台获取通过设置于城市道路的路口的摄像头采集到的路况图像。 7. The device according to claim 6, wherein the image obtaining unit comprises: an image acquisition sub-unit road, configured to obtain from a third party by the acquired internet traffic monitoring camera is provided on a city road intersection traffic image.

8.根据权利要求6-7之一所述的装置，其特征在于，所述属性信息获取单元包括： 第一属性信息获取子单元，配置用于从电子地图中获取与所述路况图像的拍摄位置对应的路段中的道路的拓扑结构、交通标识的位置； 第一属性信息配置子单元，配置用于将所述拓扑结构、交通标识的位置作为所述道路对象、交通标识对象的属性信息。 8. The apparatus according to any one of claims 6-7, wherein said attribute information acquiring unit comprises: a first sub-attribute information obtaining unit configured to obtain from an electronic photographing the road map image, position corresponding to the road link in the topology, traffic sign; attribute information of a first sub-unit configuration, the position of the configured topology, road traffic sign, as the target, the object attribute information of a traffic sign.

9.根据权利要求6所述的装置，其特征在于，所述装置还包括： 仿真对象配置单元，配置用于基于所述属性信息，配置仿真器中与所述场景对象对应的仿真对象的属性； 仿真单元，配置用于利用所述仿真器基于所述仿真对象对无人驾驶汽车的测试场景进行仿真。 9. The apparatus according to claim 6, characterized in that said apparatus further comprises: simulation object configuration unit, configured for the attribute information, the object property configuration of the simulation in the simulator corresponding to the object based on the scene ; simulation unit configured to use the simulator for the simulation object based on the unmanned vehicle test scenarios simulated.

10.根据权利要求9所述的装置，其特征在于，所述仿真器为开源车辆测试环境仿真框架OpenDrive。 10. The apparatus according to claim 9, characterized in that the simulator is the open source environment simulation test vehicle frame OpenDrive.